Protein Similarity Analysis by Wavelet Decomposition of Cellular Automata Images

In this article, a novel method of protein similarity analysis is proposed where amino acid sequences of proteins are employed to generate cellular automata images. The pairwise similarities of these images are measured from their horizontal detail images derived from wavelet decomposition by symlet wavelets. The distance metric to measure the similarity is chosen as the normalized Laplacian pyramid. From the pairwise similarity measures, a phylogenetic tree is generated and the tree is compared with two recent methods of similarity analysis. The proposed method has been proved effective to render a computationally faster and alignment-free method of protein similarity analysis.